Sample Slide Deck

Theme Preview & Feature Showcase

Academic Author

Department of Economics

2026-02-07

Bullet Points & Incremental Lists

Standard bullet points:

  • First key concept in the lecture
  • Second important idea to convey
    • Supporting detail with sub-bullet
    • Another elaboration point
  • Third takeaway for students

Incremental reveal — this appears after a pause.

Ordered Lists & Text Formatting

Steps in a research workflow:

  1. Formulate a testable hypothesis
  2. Identify an appropriate research design
  3. Collect and clean the data
  4. Estimate the model and run diagnostics
  5. Interpret results with caution

Text styles: bold, italic, inline code, hyperlink.

Use highlight classes for emphasis on key terms.

Mathematics

Inline math: The treatment effect is \(\tau = E[Y_i(1) - Y_i(0)]\).

Display equations:

\[ \hat{\beta}_{OLS} = (X'X)^{-1}X'Y \]

Aligned equations:

\[ \begin{aligned} Y_i &= \alpha + \tau D_i + X_i'\beta + \varepsilon_i \\ E[\varepsilon_i \mid D_i, X_i] &= 0 \end{aligned} \]

Code Block

# Difference-in-Differences estimation
library(fixest)

model <- feols(
  outcome ~ treated:post | unit + time,
  data = panel_data,
  cluster = ~unit
)

summary(model)

Two-Column Layout

Assumptions

  1. Parallel trends
  2. No anticipation
  3. SUTVA
  4. Common support

These are necessary for causal identification under the DiD framework.

Diagnostics

  • Pre-trend test (event study)
  • Placebo treatments
  • Sensitivity analysis
  • Robustness to controls

Always validate assumptions before interpreting estimates.

Table

Comparison of common estimators
Estimator Bias Variance MSE
OLS Low Low Low
IV None High Med
LASSO Med Low Low
Matching Low Med Med

Box Environments

Key Result: Under parallel trends, the DiD estimator is unbiased for the ATT.

Highlight: This approach extends naturally to staggered adoption settings.

Method: Estimate using two-way fixed effects with clustered standard errors at the unit level.

More Box Environments

Assumption (Parallel Trends): In the absence of treatment, the average outcomes for treated and control groups would have followed the same trend over time.

Result: The estimated ATT is 0.15 (SE = 0.04), statistically significant at the 1% level.

The credibility revolution in economics has shifted the focus from identifying assumptions to research designs that make those assumptions more plausible.

Semantic Colors & Highlights

Use semantic color classes for annotations:

  • Identified — treatment effect is well-identified
  • Biased — estimator suffers from omitted variable bias
  • Reference category — baseline comparison group

Highlight classes for emphasis:

  • Primary accent
  • Gold accent
  • Yellow accent
  • Green accent
  • Red accent